Journal article
Human error taxonomies applied to driving: A generic driver error taxonomy and its implications for intelligent transport systems
Safety Science, Vol.47(2), pp.227-237
2009
Abstract
Recent research indicates that driver error contributes to up to 75% of all roadway crashes. Despite this, only relatively little is currently known about the types of errors that drivers make and of the causal factors that contribute to these errors being made. This article presents an overview of the literature on human error in road transport. In particular, the work of three pioneers of human error research, Norman, Reason and Rasmussen, is scrutinised. An overview of the research on driver error follows, to consider the different types of errors that drivers make. It was found that all but one of these does not use a human error taxonomy. A generic driver error taxonomy is therefore proposed based upon the dominant psychological mechanisms thought to be involved. These mechanisms are: perception, attention, situation assessment, planning, and intention, memory and recall, and action execution. In addition, a taxonomy of road transport error causing factors, derived from the review of the driver error literature, is also presented. In conclusion to this article, a range of potential technological solutions that could be used to either prevent, or mitigate, the consequences of the driver errors identified are specified.
Details
- Title
- Human error taxonomies applied to driving: A generic driver error taxonomy and its implications for intelligent transport systems
- Authors
- Neville A Stanton (Author) - Brunel University, United KingdomPaul M Salmon (Author) - Brunel University, United Kingdom
- Publication details
- Safety Science, Vol.47(2), pp.227-237
- Publisher
- Elsevier BV
- Date published
- 2009
- DOI
- 10.1016/j.ssci.2008.03.006
- ISSN
- 0925-7535
- Organisation Unit
- Centre for Human Factors and Systems Science; University of the Sunshine Coast, Queensland; School of Law and Society
- Language
- English
- Record Identifier
- 99450265702621
- Output Type
- Journal article
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